{"paper_id":"569d4093-6e79-471c-bdfb-a92af83e92f0","body_text":"Pharmacological and pupillary evidence for the noradrenergic contribution to reinforcement learning in Parkinson's disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Pharmacological and pupillary evidence for the noradrenergic contribution to reinforcement learning in Parkinson's disease Claire O'Callaghan, Frank Hezemans, Naresh Subramaniam, Rong Ye, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4361233/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Aug, 2025 Read the published version in Communications Biology → Version 1 posted You are reading this latest preprint version Abstract Noradrenaline plays an integral role in learning, by optimising behavioural strategies and facilitating choice execution. Testing the noradrenergic framework of learning in the context of human diseases offers a test bed for current normative neuroscience theories and may also indicate therapeutic potential. Parkinson's disease is often considered as a model of dopamine deficits, including dopamine’s role in reinforcement learning. However, noradrenergic function is also severely impaired by Parkinson's disease, contributing to cognitive deficits. Using a single dose of the noradrenaline reuptake inhibitor atomoxetine, in people with Parkinson's disease (n=19, randomised double-blind placebo-controlled crossover design), we show improvements in learning compared to placebo. Computational modelling confirmed a substantial shift in the decision noise parameter, indicative of more exploitative choices. This response pattern closely resembled that of age-matched controls (n=26) and simulations of optimal response strategies. Pupillometry revealed increased baseline pupil diameter under atomoxetine, which correlated with behavioural improvements, and a heightened phasic pupillary response to feedback. Our findings confirm the noradrenergic contribution to reinforcement learning, and in doing so they challenge the simple interpretation of tonic-phasic locus coeruleus firing patterns based on pupillometry. Noradrenergic modulation is a potential treatment strategy for cognitive symptoms in Parkinson's disease and related disorders. Biological sciences/Neuroscience/Cognitive neuroscience Biological sciences/Neuroscience/Diseases of the nervous system/Parkinson's disease Biological sciences/Psychology/Human behaviour Biological sciences/Neuroscience/Computational neuroscience/Learning algorithms Biological sciences/Neuroscience/Learning and memory Parkinson’s disease noradrenaline locus coeruleus atomoxetine pupillometry reinforcement learning Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Published Journal Publication published 13 Aug, 2025 Read the published version in Communications Biology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4361233\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":299679613,\"identity\":\"681f5623-cb9e-4ed8-8560-367c2cd5fc18\",\"order_by\":0,\"name\":\"Claire 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